bayesian learning

Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning NeurIPS 2018 Variational Continual Learning ICLR 2018 Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task NeurIPS 2018 Wrapped Gaussian Process Regression on Riemannian Manifolds CVPR 2018 Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server JMLR 2017 Learning in POMDPs with Monte Carlo Tree Search ICML 2017 Learning Topic-Sensitive Word Representations ACL 2017 Probabilistic Inference in Hybrid Domains IJCAI 2017 Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling ACL 2017 Scalable Bayesian Rule Lists ICML 2017 Semi-Supervised Learning of a Pronunciation Dictionary from Disjoint Phonemic Transcripts and Text Interspeech 2017 Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016 Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016 Learning under uncertainty: a comparison between R-W and Bayesian approach NeurIPS 2016 Multiple Output Regression with Latent Noise JMLR 2016 Online Learning With Bayesian Classification Trees CVPR 2016 Stochastic Gradient MCMC with Stale Gradients NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015 Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity CVPR 2015 Variational Dropout and the Local Reparameterization Trick NeurIPS 2015 Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes? AISTATS 2014 Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NeurIPS 2014 Bayes-Adaptive Simulation-based Search with Value Function Approximation NeurIPS 2014 Bayesian Co-Boosting for Multi-modal Gesture Recognition JMLR 2014